Enterprise technology & artificial intelligence
Modern, secure IT environments — with AI delivered, not promised.
The Power of LogicNest:
Intelligence, Delivered.
Twenty-five years delivering enterprise technology. Five disciplines, one delivery model, and teams in the United States and India working the clock in your favour.
Who is LogicNest
Built to carry a programme end to end
Our architects, engineers, ERP consultants, data specialists and security professionals work from one plan, report to one accountability, and stay through production — not to a demo, to a running system with an owner.
That structure is deliberate. It means the security review happens at architecture rather than two weeks before launch, the AI use case is scoped against data someone has actually inspected, and the migration business case is modelled by the people who will operate the result.
Most technology failures are not technical. They happen in the gaps — between the team that holds the data and the team that holds the platform, between the vendor who built it and the vendor who runs it. We removed the gaps.
Services
Five disciplines. One delivery model.
Depth in each, and a single point of accountability across all of them. Most of the problems we are called about sit between two — which is precisely why we run them together.
- 01 AI & Data Intelligence Readiness assessment through to production systems: agentic automation, retrieval-grounded assistants, document intelligence, forecasting — and the data platform underneath that makes any of it possible. Agents · RAG · MLOps · Lakehouse · Governance
- 02 Cloud & Infrastructure Private cloud, migration waves, disaster recovery and managed operations — sized against the workload you actually run, with run-cost modelled before anything moves. Private cloud · Migration · DRaaS · FinOps
- 03 Software Development Enterprise applications, web and mobile, legacy modernisation and the integration work that is usually the real bottleneck. Built so a different team can still extend it in three years. Enterprise apps · Modernisation · Integration
- 04 ERP & Business Systems Selection, implementation, integration and application maintenance across the major platforms. We hold no reseller agreements, so the recommendation is the entire product you are buying. Selection · Implementation · Master data
- 05 Cybersecurity Posture assessment, identity and access, cloud and infrastructure security, compliance readiness. Designed in at architecture by the people who will also operate it. Posture · Identity · Cloud security · Compliance
The AI practice
Most AI pilots never reach production. Ours are scoped to.
The distance between a working demo and a system your business depends on is data access, integration, security review and someone to run it at 3am. We build across all of those — which is the whole reason our AI work ships.
- Assessment before architecture. Two weeks to a costed roadmap, and sometimes the finding is that the highest-value work isn't AI at all.
- Evaluation from day one. Accuracy and spend instrumented before launch, not after the first complaint.
- Your data trains nothing. Enterprise endpoints with zero-retention terms, or fully self-hosted where policy requires it.
- Permissions inherited, not reinvented. An assistant shows a user only what that user could already access.
Figures reflect the LogicNest delivery team as of 2026.
Where we work
Where technology meets operations
We do not sell domain expertise — you already have that. We sell the engineering between your specialists and your systems. Across every sector the pattern is the same: platforms that were never designed to talk to each other, and decisions waiting on data that takes a week to assemble.
Oil & Gas
Upstream, midstream and downstream. Production surveillance built on historian data, well and facility analytics, land and lease document intelligence, emissions and regulatory reporting, OT/IT convergence, and the joint-venture accounting that makes ERP genuinely hard in this sector.
Explore the sectorEnergy & Power
Generation and grid-adjacent operations: asset monitoring at scale, outage and capacity forecasting, and the integration work between operational systems and the analytics layer.
Utilities
SCADA and telemetry data, consumption analytics, loss detection, and resilience planning for systems that cannot be taken offline.
Manufacturing
ERP and shop-floor integration, demand and capacity forecasting, and the master-data work underneath both.
Real Estate
Building systems integration, tenant and operations platforms, GIS and spatial data, portfolio reporting.
Technology landscape
We work across the platforms you already run
We hold no reseller agreements and take no vendor commissions, so what follows is a description of where our engineers are experienced — not a list of things we are paid to recommend.
Cloud & platform
- AWS
- Microsoft Azure
- Google Cloud
- VMware / private cloud
- Kubernetes
- Terraform
Data & AI
- Databricks
- Snowflake
- Microsoft Fabric
- Azure OpenAI / Bedrock
- Open-weight models, self-hosted
- Vector & graph stores
Operational data
- OSIsoft PI / AVEVA
- OPC UA
- Historians & time series
- SCADA integration
- IoT & edge gateways
- Esri / GIS
Business systems
- Major ERP platforms
- Field & asset management
- Document management
- Identity providers
- Integration & iPaaS
- Reporting & BI
How we engage
Three ways to start, all of them concrete
No open-ended discovery, no six-week statement of work before anything happens. Every engagement begins with something that has a scope, a date and a deliverable.
Assessment
Two to four weeks, fixed scope, fixed fee. You get a findings document and a costed roadmap — yours to keep whether or not you use us to deliver it.
Project
Defined outcome, defined date. Our team, our accountability, your systems. Documentation and runbooks are deliverables, not afterthoughts.
Managed
We run it. Named engineers who know your estate, agreed response times, monthly reporting, and a standing quarterly review.
How delivery runs
The same four phases, whichever practice you start with
Assess
Interviews, inventory, and a candidate list scored against value and feasibility. Findings document plus costed roadmap.
2–4 weeksProve
One use case, built against real data in a controlled environment, measured against criteria agreed before we start.
4–8 weeksProductionise
Security review, integration into live systems, monitoring, evaluation harness, documentation and training. The phase most vendors skip.
8–16 weeksOperate
Managed support and optimisation with named engineers — or a clean handover to your team, with the runbooks to do it.
Ongoing
The layer under everything
Nothing intelligent runs on disorganised data
Pipelines, lakehouse architecture, quality, lineage, cataloguing and access control. It is the least glamorous thing we build and the reason the rest of it works — the agents that need governed access, the forecasts that need clean history, the assistants that must respect who is allowed to see what.
“We would rather lose the AI project and keep the client. If the assessment says the highest-value work is fixing your data platform first, that is what the assessment will say.”
Delivery model
One plan, five practices, no handoffs
Every engagement runs through the same spine. Which practices join at which stage changes; the accountability and the gates do not.
Each gate is a written go/no-go with the evidence attached. If the proof stage does not clear the criteria we agreed before starting, we report that rather than quietly rescoping.
Outcomes
What our engagements are built to change
The three patterns below describe work we are set up to deliver and the measures we hold ourselves to. Named client results are available under NDA at proposal stage — ask, and we will be specific.
Production surveillance that runs itself
Historian, well-test and field data joined into one governed model, with exception detection replacing the daily manual scan. Target: engineers reviewing exceptions rather than assembling spreadsheets, and deferment identified the same day rather than the following week.
Paperwork turned into structured data
Invoices, contracts, inspection reports and scanned records extracted with confidence scoring and a human review queue for anything below threshold. Target: the majority of documents cleared without a person touching them, with every extraction auditable back to the page.
Migrations that land on budget
Run-cost modelled per workload before anything moves, waves planned against real dependencies, and spend instrumented from day one. Target: an invoice that matches the business case, and a cost report tying spend to workloads and owners every month.
Written as commitments rather than case studies, because we do not publish client outcomes without written permission.
Assurance
How we work with your risk, legal and audit teams
The questions that stall technology purchases are rarely technical. These are the answers we lead with.
Data handling
Defined data locations, named sub-processors, and zero-retention terms with model providers on AI engagements. We will share the contract language before you ask for it.
Access & identity
Least-privilege access for our engineers, tied to your identity provider, with joiners and leavers handled on your process rather than ours.
Documentation
Architecture decisions, runbooks, evaluation results and handover training are contracted deliverables, so an audit finds evidence rather than tribal knowledge.
Continuity
Named engineers with named backups, and knowledge held in documentation rather than in one person's head. You should be able to replace us without a gap.
Security by design
The security practice reviews at architecture on every engagement, whichever practice is leading it. Not a gate at the end.
IP ownership
Code, configuration, prompts, pipelines and documentation are yours. We do not build on anything that would trap you with us.
Questions we get asked
Straight answers
How quickly can you start?
Assessments typically start within two to three weeks of a signed order. If something is genuinely on fire we will tell you honestly whether we can move faster or whether you need an incident response firm instead.
Are you big enough for our programme?
For a five-practice programme with named accountability, yes. For a thousand-seat global rollout, we would rather say so than take it and struggle. Ask us for the honest read on scale at proposal stage — you will get one.
Do you work onsite?
For Gulf Coast and Texas clients, regularly. Elsewhere we work remotely with onsite time at the points where it matters — discovery, cutover, and handover.
Can we start small?
That is the design. Every practice has a fixed-fee assessment as its entry point, and the findings are yours whether or not you continue with us.
Who owns what you build?
You do — code, prompts, configuration, infrastructure definitions and documentation. Handover with runbooks and training is a deliverable in every engagement.
Do you take vendor commissions?
No. We hold no reseller agreements, which is why our ERP and cloud recommendations are worth what you are paying for them.
Global delivery
Two time zones, working in your favour
Client-facing leads and architecture in the United States. Engineering depth in India. One plan, one set of standards, and a handover at the end of each day rather than at the end of each sprint.
It is not offshoring work to save money and hoping quality holds. It is a delivery model where the assessment you approve on a Tuesday afternoon has progress against it by Wednesday morning.
- United States — engagement leadership, architecture, client-facing delivery and all commercial accountability.
- India — engineering, data and platform build, testing and managed operations, on the same tooling and the same review gates.
- One standard — the same architecture decision records, the same code review, the same definition of done, wherever the work happens.
- Overlap by design — scheduled hours where both teams are live, so handovers are conversations rather than tickets.
The people on your engagement
You will know their names before you sign
Not a pitch team who hands you to someone else. These are the roles that show up on a LogicNest programme, what each one owns, and who you will be talking to week to week.
Engagement lead
Single point of accountability
Owns the plan, the gates and the commercials. The person you call when something is wrong, and the one who tells you before you have to ask.
Principal architect
Design authority
Holds the architecture across practices so the AI design, the platform it runs on and the controls around it are one decision rather than three.
Data & AI lead
Delivery
Runs the assessment, the proof of value and the evaluation harness. Answers for accuracy and for inference spend, in the same meeting.
Security lead
Assurance
In the room at architecture, not at the end. Owns the conversation with your risk and audit teams so it is not yours to translate.
Named profiles and photographs are provided at proposal stage — you meet the actual team before you commit.
Insights
What we have learned doing the work
Not vendor summaries or conference recaps. Specific writing about where these programmes actually fail, from the engineers who have had to fix them.
AI & Data IntelligenceWhy AI pilots stall at the data layer
Four questions that predict whether a pilot reaches production — and what to do when the answer to any of them is no.
Read — 12 min read
Cloud & InfrastructureWhat a cloud migration actually costs
The business case is built on list prices and the invoice is built on behaviour. Here is where the gap comes from, line by line.
Read — 10 min read
Oil & GasGetting historian data out without opening the plant
The OT/IT boundary in upstream and midstream operations, and an architecture your process-safety people will actually sign.
Read — 14 min read
Next step
Tell us what isn't working.
Thirty minutes with an engineer, not a salesperson. If we are not the right fit we will say so and point you somewhere better.